Uploaded byTristan Roddis
Linked data at the Science Museum
The document discusses the integration of linked data into the collections management systems at the Science Museum to enhance data connectivity and extensibility. It outlines the challenges faced, such as identifiers stability and the need for a mindset change regarding linked data's capabilities. The future direction emphasizes leveraging existing data sources and expanding to linked open data through various ontologies and public APIs.
Linked data at the Science Museum
- 1. Linked Data at TheScience Museum Tristan Roddis, Cogapp Daniel Evans, Science Museum MCN 2012, Seattle
- 2. Agenda The context The bigidea Why linked data? The approach The challenges Where next? Questions
- 3.
- 9. Specifically Collections Management System(MultiMimsy XG) Digital Asset Management System (iBase) Archives Management System (AdLib) Web Content Management System (Sitecore) Legacy Web content (XML files) Etc.
- 10. Sitecore Mimsy CMS CMS iBase DAM AdLib AMS Legacy docs
- 11.
- 12. Extract data fromall silos and connect Use Linked Data for extensibility
- 13. Sitecore Mimsy CMS CMS Triple store iBase DAM AdLib AMS Legacy docs
- 14.
- 15. A brief historyof data Relational Hierarchical Graph
- 16. Linked Data iseasy! foaf:firstName cog:tristan “Tristan” subject predicate object <http://data.cogapp.com/id/tristan> <http://xmlns.com/foaf/0.1/firstName> "Tristan".
- 19. Linked Data ingredients RDFtriples Triple-store SPARQL endpoint (Inferencing engine)
- 20. Benefits of LinkedData Flexible storage Flexible querying Evolution of data Standard format and interface Linking to the web of data
- 22.
- 23. Sitecore Mimsy CMS CMS COBOAT Workflow hook Triple store COBOAT API iBase + DAM rdflib AdLib One-off import AMS Legacy docs
- 27.
- 28. Identifiers Stability 303 redirects Opaque versushuman-readable http://data.sciencemuseum.org.uk/id/objects/smxg-12345
- 30.
- 31. Ontologies Dublin Core (DC) DublinCore Terms (DCT)
- 32. Ontologies Dublin Core (DC) DublinCore Terms (DCT) Friend Of A Friend (FOAF)
- 33. Ontologies Dublin Core (DC) DublinCore Terms (DCT) Friend Of A Friend (FOAF) Simple Knowledge Organization System (SKOS)
- 34. Ontologies Dublin Core (DC) DublinCore Terms (DCT) Friend Of A Friend (FOAF) Simple Knowledge Organization System (SKOS) CIDOC Conceptual Reference Model (CIDOC CRM)
- 35. Ontologies Dublin Core (DC) DublinCore Terms (DCT) Friend Of A Friend (FOAF) Simple Knowledge Organization System (SKOS) CIDOC Conceptual Reference Model (CIDOC CRM) Europeana Data Model (EDM)
- 36. Ontologies Dublin Core (DC) DublinCore Terms (DCT) Friend Of A Friend (FOAF) Simple Knowledge Organization System (SKOS) CIDOC Conceptual Reference Model (CIDOC CRM) Europeana Data Model (EDM) schema.org
- 37. Ontologies Dublin Core (DC) DublinCore Terms (DCT) Friend Of A Friend (FOAF) Simple Knowledge Organization System (SKOS) CIDOC Conceptual Reference Model (CIDOC CRM) Europeana Data Model (EDM) schema.org Etc.
- 41. Linked Data isstill young Immature tools and technology Small pool of experts Mindset change
- 42. Linked Data doesn’tsolve everything Filtering tasks Reconciliation tasks Exposes inconsistencies Exposes copyright issues
- 43.
- 44. Where next? Data opportunities: More sources (Sitecore, legacy sites, new content) More data from existing sources (reconcilliation between systems, turning literal strings into nodes) From Linked Data to Linked Open Data: link to DBpedia, Geonames, VIAF, BNB, etc. Inferencing to expose data via different ontologies
- 45. Where next Publishing opportunities: Public SPARQL Endpoint REST API Website Pull in UGC Pull in external data
- 46. Geonames DBPedia Sitecore Web pages Mimsy CMS REST API CMS UGC Triple store SPARQL iBase DAM AdLib AMS Legacy docs
- 47.
Editor's Notes
- #2 Daniel can’t be here
- #4 In common with other institutions, SM has disparate data silos
- #13 Not consolidation. Instead: scheduled, repeatable extraction
- #17 This is called RDFEverything is a tripleUnique URIsTriples interconnect to form a graph
- #19 Individual triples with the same subject or object interconnect to form a graph of data
- #20 Inferencing: e.g. hasMother, hasFather: hasParent
- #21 Storage: no schema changesQuerying: no inherent hierarchyEvolution: easy to change or layer or mergeStandard: works regardless of underlying systemsLinking: LD->LOD. Unambiguously connect
- #22 http://richard.cyganiak.de/2007/10/lod/
- #24 Overall scheme: Collections Management System (MultiMimsy XG) = RDDMS = COBOAT Digital Asset Management System (iBase) = RDDMS = COBOAT Archives Management System (AdLib) = REST API = custom Python scripts (rdflib) Web Content Management System (Sitecore) = .NET = custom workflow hook (dotNetRDF) Legacy Web content (XML files) = custom script for one-off importSome channels still pending
- #26 Example query
- #27 Results shown as a graph
- #29 Explain structure of e.g. http://data.sciencemuseum.org.uk/id/agents/sm-12345Mention Cool URIs, and UK government guidelinesPossible example of opaque vs non
- #30 http://www.w3.org/TR/cooluris/http://data.gov.uk/resources/urishttp://www.cabinetoffice.gov.uk/resource-library/designing-uri-sets-uk-public-sector
- #38 Mention that we talked to the BL, the BM, archives hub, Kasabi
- #39 Discussion about design principle: minimise number of different classes; reuse popular ontologies; model our domain; limit repetition;
- #40 Popular ontologies: FOAF
- #41 Useful ontology: SKOSMention unresolved questions e.g. how much duplication of predicates; how to map to others – inferencing?
- #42 Brand new in terms of adoptionTools: subtle differences between systems. Inferencing not standard.Experts: compare finding info on Jena versus find info on Apache web serverMindset change: lots of relational database developers, comparatively few for LD
- #43 Filtering: only public data should be exposed (at both item and field level)Reconciliation: making sure identifiers sync; making sure data links up(i.e. no orphaned content)Inconsistencies: example of many source predicates for ‘maker’ collapsed to a few in final structure; example of different uses of similar systems such as iBaseBtLvsiBase IngeniousCopyright: issue of text or images not owned by institution: triple store would need to only have references if made available as CC0
- #46 UGC example: crowdsourced Babbage transcriptionsExternal example: wikipedia bios for people, geonames data for places
- #47 Verbal summary: the move to linked data can be challenging, but is exciting and liberating